708 件 ・ 関連度順
概要と使いどころ
当用户需要对寿险理赔申请资料做结构化受理预审、材料完整性检查、死亡事实与身故原因相关证明核验、申请人和受益人资格资料检查、补件清单整理或受理前问题识别时使用本 skill。适用于检查理赔申请书、被保险人身份证明、申请人或受益人身份证明、银行卡信息、死亡证明、户籍注销证明、火化证明、亲属关系证明、受益人证明、医院病历、抢救记录、出院记录、公安或司法证明、事故证明、殡葬资料等是否齐全、清晰、有效、相互一致，并输出适合理赔受理、补件沟通和内部留痕的检查结果。
日本語の概要は準備中です。原文の説明を表示しています。
当用户需要对重疾险理赔申请资料进行结构化受理检查时使用本 skill。它用于识别理赔申请书、身份证明、银行卡信息、诊断证明、出院记录、住院病历、病理报告、手术记录、影像报告、专项检查报告等与重大疾病责任认定相关的关键材料是否齐全、清晰、有效、相互一致，并输出补件清单、受理前检查结果和跟进建议。
日本語の概要は準備中です。原文の説明を表示しています。
当用户需要协助理赔沟通时使用此 skill。适用于理赔申请指导、与保险公司沟通话术、理赔异议处理等场景。
日本語の概要は準備中です。原文の説明を表示しています。
当用户需要对医疗险理赔申请资料进行结构化受理检查时使用本 skill。它用于识别理赔申请书、身份证明、银行卡信息、病历、出院记录、费用清单、发票、结算单、检查报告、诊断证明等材料是否齐全、清晰、有效、相互一致，并输出补件清单、受理前检查结果和跟进建议。
日本語の概要は準備中です。原文の説明を表示しています。
Evaluates insurtech business models with distribution innovation, underwriting technology, and claims automation. Use when analyzing insurtech, evaluating digital insurance, or assessing insurance technology.
日本語の概要は準備中です。原文の説明を表示しています。
Query the Bear EHR database using the semantic layer. Use when asked about clients, billing, appointments, insurance, clinical data, procedures, scheduling, programs, staff, vitals, diagnoses, revenue, claims, or any data question about the Bear application.
日本語の概要は準備中です。原文の説明を表示しています。
Structures cyber insurance evaluation with coverage assessment, limit adequacy, and claims scenario analysis. Use when evaluating cyber coverage, analyzing policy terms, or assessing cyber insurance adequacy.
日本語の概要は準備中です。原文の説明を表示しています。
Configures JWT Bearer authentication for .NET APIs. Includes token generation, validation, refresh tokens, and user context extraction from claims.
日本語の概要は準備中です。原文の説明を表示しています。
Traditional Chinese internal arts — tai chi chuan and qigong — as transmitted by classical lineages (Chen, Yang, Wu, Wu/Hao, Sun for tai chi; Ba Duan Jin, Yi Jin Jing, Liu Zi Jue, Wu Qin Xi, and other named sets for qigong) with an emphasis on alignment, rooted stance, breath-posture-mind coordination (the three harmonies), and the traditional lineage voice that Dr. Yang Jwing-Ming's YMAA line preserves. Also covers the safety boundary between traditional practice and clinical "medical qigong" claims. Use for queries about tai chi form learning, qigong set selection, internal-arts pedagogy, and the practical question of where to start.
日本語の概要は準備中です。原文の説明を表示しています。
Climate physics, forcing, feedback, and attribution. Covers the greenhouse effect and radiative forcing, climate sensitivity, fast and slow feedbacks, the paleoclimate record, detection and attribution science, regional climate impacts, and the distinction between weather, climate variability, and forced climate change. Use when reasoning about global warming mechanisms, interpreting temperature or CO2 records, evaluating attribution claims for extreme events, or distinguishing signal from natural variability.
日本語の概要は準備中です。原文の説明を表示しています。
A/B testing, randomization, sample size calculation, confounding control, and causal inference for data science. Covers the full experimental lifecycle from hypothesis formulation through power analysis, randomization strategies, blocking, factorial designs, sequential testing, and the potential outcomes framework for causal claims. Use when designing experiments, planning A/B tests, calculating sample sizes, or reasoning about causation from data.
日本語の概要は準備中です。原文の説明を表示しています。
Adversarial spec-compliance PR review — cross-references diffs against approved specs, verifies runtime claims against source, detects competing PRs, audits scope/convention compliance. Use before merging.
日本語の概要は準備中です。原文の説明を表示しています。
Triage a GitHub issue filed against skillsaw — classify it (bug, feature, docs, question, other), verify its claims against the codebase, enrich it with missing details, and post one structured triage comment. Use when triaging and labeling incoming issues, not to fix them.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the primary outcome is creating publishable source-attributed content from URLs or supplied material, including research summaries, articles, briefs, and posts whose factual claims and quotations need reader-visible, verifiable citations.
日本語の概要は準備中です。原文の説明を表示しています。
Rigorous self-assessment checklist before marking any task as complete. Use when about to claim task completion, before final commit, when user asks "is it done?", or when transitioning from implementation to reporting. Prevents premature completion claims by requiring evidence for every assertion.
日本語の概要は準備中です。原文の説明を表示しています。
Audit documentation claims against implementation and authoritative repository evidence. Use when checking whether README, architecture, configuration, API, usage, or feature documentation is stale, incomplete, contradicted by code, missing implemented behavior, or inconsistent with a normative contract.
日本語の概要は準備中です。原文の説明を表示しています。
Runs several language models as independent coders on one labeling or discovery task and treats disagreement as data. Covers diverse panel assembly, independent voting, consensus rules, Cohen’s and Fleiss kappa, Krippendorff’s alpha, correlated-error limits on validity claims, human validation, and reporting. Use when the user asks about a council, panel, ensemble, or jury of models, how to combine model labels, or what kappa or alpha to report for model coders. Single-model codebook and validation work goes to text-classification, per-item confidence to llm-calibration-logprobs.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze competing products and turn the market gap into credible positioning, messaging angles, and social campaign claims. Use when comparing competitors, writing alternative pages, sharpening product positioning, or planning campaigns against a category narrative.
日本語の概要は準備中です。原文の説明を表示しています。
Fact-check manuscript claims against their cited sources in a per-source Markdown knowledge base. Use to audit claim support, overclaiming, direction, scope, and misattribution after source intake is complete.
日本語の概要は準備中です。原文の説明を表示しています。
Product-only Red Team audit of the FMT/IWE platform: source, manifests, setup/update paths, CI and release provenance, agent permissions and memory, hooks, runtime, roles, schedulers, Day Open/Close, and regression claims. Use before merging or publishing a release, after changes to updater/runtime/security behavior, or when verifying a reported platform defect. Excludes real consumer workspaces and personal customizations; use repository-owned code and synthetic disposable fixtures only.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user asks for journal recommendation, 选刊, 投稿期刊筛选, 期刊匹配, 适合投稿的期刊, 投哪个期刊, or wants 3-5 suitable journals for a manuscript based on an abstract, discipline, CAS/JCR ranking, impact factor, Aims & Scope, review speed, OA/APC, and publication-risk checks.
日本語の概要は準備中です。原文の説明を表示しています。
Use after an Anabasis v2 comparison, checkpoint or system change, and before any sentence claims that a harness, a model or a patch improved something. States what one reading may be said to show: the identities it was made under, the counts kept apart, whether it was repeated, which part of a harness it belongs to, whether a mechanism was live in the run, and whether the measurement is valid as distinct from whether it was exploited. Ends in one fixed report.
日本語の概要は準備中です。原文の説明を表示しています。
Systematically deconstruct written content into verifiable claims, validate each using search/documentation, and facilitate informed discussion through structured interviewing.
日本語の概要は準備中です。原文の説明を表示しています。
Maintain required external authorization decisions, gatekeeper and validator hooks, the HTTP JSON plugin, reusable parsers, and protected-request E2E coverage. Excludes credential authentication and claims enrichment.
日本語の概要は準備中です。原文の説明を表示しています。